We have canonical metaphors for organisations:
Whilst reading Helen Czerski’s Blue Machine, it struck me that we need a similar canonical metaphor list for protocols.
Some candidates:
There are two key emotions that drive my research habits: wonder, and pure unadulterated rage
Hmmm.
AI must be a liberating equalizer for humanity. Capable, reliable assistance should reach everyone with a phone or computer, giving them greater command of their time, information and choices. As we prepare for a world with super intelligence, sovereignty must extend to ordinary people’s lives.
And the shoulders that Steve Jobs, Bill Gates, and others stood on were not those of pocket-protector-wearing nerds clocking into jobs at Lockheed, but young and freaky computer scientists. My friend John Markoff’s book What the Dormouse Said is all about how the counterculture set the tone for the Valley during its tremendous growth years. When we spoke this week, Markoff noted that the Valley’s transition point from a defense-oriented industry to one shaped by counterculture values rose from three pivotal computer labs—AI pioneer John McCarthy’s Stanford lab, the Stanford Research Institute, which hosted Douglas Engelbart’s groundbreaking GUI innovations; and Kay’s Xerox PARC, which essentially set the foundation for the computers that we all use today.
Take dopamine sites and scale them up through the social stack (individuals to packs to troops to tribes to imagined communities); what does one get?
Many such cases.
i basically dont have time to write anymore. maybe ill release something once every 1-2 months, and even that is a stretch. im now squarely incapable of doing anything near my prior 1-2 week/article cadence. it was a good 2.5 year run!
owl on X: i basically dont have time to write anymore. / X ↗
Protocol thinking is way more distinct from product thinking than I appreciated. Not different by degree. Not even different by kind. It’s different at the paradigmatic level.
First, traditional product thinking is outcome-based. One picks a target state, evaluates risks, and constructs archetypical cases to steer toward it. Success is arriving at the intended destination.
Protocol thinking optimises for something else entirely: an expansion of the moves available to players of the game. The protocol designer does have near-term goals, such as interoperability, legibility, and a low cost of compliance, but beyond them, they deliberately under-determine what gets built. That restraint is the point. Every outcome specified is a move taken off the board for someone else.
This is why indexing on outcomes, or even a cluster of them, fails. The upside a good protocol unlocks isn’t just hard to predict; it’s unnameable in advance. Steering toward a target state, however carefully chosen, narrows the space that’s meant to be widening. The question is whether others can now do surprising things in surprising ways neither they nor we could have specified beforehand.
Second, because protocol thinking solves for, essentially, unanticipated upside and future ecosystem optionality, one’s stance toward value capture and accumulated credit must change dramatically. Not softened. Abandoned.
Credit requires attribution, and attribution requires a nameable outcome. The moment one starts keeping score, one is pulled back toward the outcomes one can point at, which is to say back toward product thinking.
Value capture does the same damage more directly: every toll taken is a tax on the very moves the protocol was meant to make available. The aim is to expand others’ agency, not enlarge the designer’s share.
Protocol thinking in this sense asks for something product thinking never does: surrendering one’s own agency, credit accumulation and value capture in exchange for others’ capacity to accrue them.
Third, inbound changes must be guarded far more judiciously. In product, a feature request is a signal to weigh against a roadmap. In a protocol, a proposed change is an amendment to the rules everyone plays by, and it deserves scrutiny proportional to that, especially when it foregrounds someone’s value capture.
Some open-source projects have closed themselves to outside contributions rather than drown in evaluating them. That’s one answer. The better one is explicit criteria and quality gates that make the bar legible before anything is proposed. The bar must be high because, in a protocol, the letter and the spirit have to be synonymous.
Product teams can lean on intent, norms, and a terms-of-service page. Protocols can’t. Anything the rules permit will eventually be done; anything extractable will be extracted, as maximal extractable value shows with grim reliability. A change that’s harmless in spirit but exploitable in letter is simply exploitable. If the spirit isn’t encoded in the letter, it doesn’t exist.
For cognitive security, it is critical to air gap one’s self on a regular basis. Disconnect, disappear, go off the grid, unplug; have recurring hard switches into embodied activities that require no thought or agency.
Anything new or novel that is software-related should either take minutes / hours or require years. The middle ground is becoming a legitimate killing field. See Jev, as an example; multiple years eclipsed in days post-release.
Mavericks, misfits, revolutionaries, heretics, infidels; never a better time to be such a person.
Consider, for instance, the rise of molecular biology as a discipline. We think of Watson and Crick as molecular biologists, not as an ornithologist and a physicist. The first molecular biologists were a motley crew of misfits and revolutionaries with no particularly relevant training, many of them ex-physicists. These physicists didn't waste much time identifying themselves as physicists any more. They viewed themselves as a new kind of biologist. They burned their bridges. Max Delbrück dropped physics and started studying phage replication because it seemed like the fastest, best way to crack the molecular basis of heredity. It's hard to imagine molecular biology making such dramatic progress if it had involved forming interdisciplinary teams of physicists and biologists. The molecular biologists were viewed as naive infidels.
I’m at the point where I want to start extending the Blygger protocol to accommodate Hermann Hesse’s Glass Bead Game.
The first thing I have to remind myself is that Product Brain must evolve to Protocol Brain. Don’t make the client or the platform; make the protocol-ish engine that can power numerous arbitrary, value-adding manifestations of clients and platforms. To do that, I’ll take an Amazonian approach and work backwards.
In Hesse’s novel, a Glass Bead Game is played by Castalia’s scholars using a symbolic language that links ideas from every discipline, such as a musical theme, a mathematical proof, or a line of poetry. A player opens with a motif, then develops and transforms it through variations, counterpoints and correspondences across fields, much like composing a fugue.
The aim isn’t to win but to create a game of maximum harmony, elegance and insight, revealing the hidden unity of all knowledge. A great game is judged as a work of art and is also experienced as contemplation, close to prayer.
Happily, Blygger’s ethos and resulting protocol—blogs × wikis × Twitter × git changelogs, built on static files and RSS—provide the primitives to bring GBGs to life on the web, today.
Let’s pretend that one of The Protocol Institute’s Special Interest Groups (SIGs) is extending their roster of events. On a weekly basis, they will be hosting a Glass Bead Game.
The Game functions as follows. The two players involved agree to an exchange which the SIG has a particular interest in. Let’s say the SIG provides a prompt or brief in advance.
The Game begins. The first turn is a Player making an opening move using their own Blyg. Perhaps they iterate through a fragment or piece together a thread. When time runs out, the move is locked in.
The other Player responds via their own Blyg. They may respond directly with a fragment. They might transclude a thread from the Blyg of someone else in the SIG (a number of whom are watching the Game unfold live, hanging out on Discord).
The exchanges go back and forth, with fragments, threads, transclusions, stubs, and off-Blyg excerpts all woven into a dense tapestry of live thought.
At the close of the Game, the entire structure is itself locked up, and then becomes a part of the cultural mosaic, and informs both ongoing Blygging and future Games.
Extending Blygger for GBGs
Working backwards from the Game, the protocol needs to supply a handful of things:
Almost all of this already exists.
stub_ofTiming, turn order, spectators and judging stay out of the protocol entirely, just as AI does.
Only two things are missing:
Membership. A new optional field, game_of, names the brief. Clients that don’t understand it ignore it, so a move still reads as an ordinary stub everywhere else.
Multiple parents. Synthesis moves build on more than one prior move, but stub_of names a single target. Relaxing it to accept several means one Webmention per parent. A more conservative route leaves stub_of alone and treats a move’s transclusions as its extra parents.
A valid move, then, is a pinned L2 item that carries game_of and stubs at least one prior move in the same Game; an opening move stubs the brief. The pinned version is the move, so later edits to the live item don’t touch the Game. The protocol only defines what counts. The SIG’s Game client checks who played and when, and leaves anything invalid out of the record.
A few questions remain open.
game_of really a general “convened by” field that salons and reading groups could reuse?The best longevity protocol is to live like someone who isn’t worried about money.
Alignment incidents, such as agentic swarms, aren’t the true harbingers of AGI. Humour is. When a machine can tell a stonker of a joke to the same standard as a comedian during a set or whilst bantering on a podcast, then we’ll have issues.
In the meantime, we’ll have to make do with material like this: “We live in a wild era. I bought a smart mattress that tracks my sleep cycles, and now it sends weekly performance reports to my phone. Nothing ruins your Monday morning quite like your bed giving you a C-minus in resting.”
No backsies; this little stream of thoughts-as-notes has entered the Blygosphere.
Hmmm.
And since, thanks to Enlightenment, citizenship (membership in the political community), nationality, and humanity had been synthetically merged, being expelled from citizenship meant, quite literally, exclusion from humanity. Hence civic death was necessarily followed by natural death, that is, violent death, or death tout court. Fascist or Nazi genocide was not preceded by legal condemnation (not even in the stunted and fraudulent shape of the so-called administrative verdicts of Cheka “tribunals”): it was the “naturalization” of a moral judgment that deemed some types of human condition inferior. And since there was no protection outside citizenship, lack of citizenship had become the cause of the cessation of the necessary precondition of the human condition—life.
Uncomfortable consumer software ground truths:
Hmmm.
My emotions were never “irrational”—they were just locally optimal.
Capital-labour-technology dynamics seem poised to go to some weird, truly unprecedented places.
Under either scenario, the ideological position of the homoploutic class as a legitimate meritocracy will collapse. Under entrenchment, the homoploutic claim to merit becomes untenable because there is no path to entry: Once inheritance is the only way into the top decile of capitalists, such a class can’t credibly describe itself as meritocratic, no matter how hard-working. Under dissolution, if education no longer commands a wage premium, there is no longer any meritorious activity to point at — one is simply an owner of capital, as one’s great-grandfather was. In the first case the asset value of the class survives, but the flow into it stops. In the second, both go.
Asking well is really, really, really hard, and kind of exhausting, though.
There it is, the radical offering of 21st century computing, here at last: ask for what you want. It takes practice! And, honestly, a certain audacity.
'Ask for what you want' is a key skill for the 21st century ↗
Hmmm.
In short, model capability is good enough that compelling products — products that actually have moats — can now be built, and from a business perspective it would do Anthropic and OpenAI good to devote more of their resources to actually building such products.
Putting this here (instead of there) so I don’t forget, and so others remember.
People think that the main benefit of writing in the public domain is “exposure”, or that it compels you to think with more clarity/rigour.
Both are true, but both are subservient to the fact that writing in public leads to a handful of unexpected and meaningful relationships.
If, as Ben Thompson says, consumers don’t want to pay for software and don’t care about being productive, then the path forward is obvious: provide a personal agent that sweeps into one’s life and effs it up for free.
Donald Stokes identified four research quadrants, with axes based on whether one is seeking fundamental understanding and whether one is considering use.
What is increasingly interesting to me is the transitions between these quadrants. There are three traditional routes.
First, there’s the case where fundamental discovery leads to use. Quantum mechanics was worked out in the 1920s as pure physics, and two decades later it made the transistor possible.
Second, there’s the case where the realities of application and practice are pacing the frontier and our elucidation of fundamental truths is scrambling to catch up. The steam engine was running for a century before Carnot and his successors worked out the thermodynamics explaining why.
Third, there’s the case where play turns up something one of the other quadrants picks up. Feynman’s idle maths on a wobbling cafeteria plate led him back to the electron spin problems behind his Nobel.
Historically, these routes between quadrants were structurally enforced by the relationships between the forces of capital, labour and technology. Some definitions:
Generally speaking, research moved at the speed of people. Even with Manhattan projects and fast initiatives, people were the constraint. That’s changed.
The schtick is that technology and capital are increasingly aligning to minimise the reliance on labour supply. That’s why there are big bets being made on 1) personal productivity agents and 2) autonomous meta-science and experimentation. Maximised personal productivity plus accelerated learning loops is the holy grail of the permanent overcast.
Of course, it’s not as simple as that and the world will be curiously playable to a greater extent than ever before. That’s because different paths between the quadrants will dominate and the time taken to walk those paths will be slashed to near-zero. For example:
If we’re truly entering the Liveness machine, we’re going to have to play seriously. Which means that Feynman’s quadrant, the very one Stokes under-appreciated, will matter much more than we ever expected.
Cool and all, and there definitely will be absolutely zero chance of any negative higher order effects, at all, over any timespan.
Cloud seeding is undertaken by dispersing substances into the air that serve as cloud condensation or ice nuclei. Common agents include silver iodide, potassium iodide, and dry ice, with hygroscopic materials like table salt gaining popularity due to their ability to attract moisture. Techniques vary from static seeding, which encourages ice particle formation in supercooled clouds to increase precipitation, to dynamic seeding, designed to enhance convective cloud development through the release of latent heat.
Hmmm.
"Enshittification" is a sort of "safe horny" term for what is really just outright impoverishment and declining living standards due to economic insolvency from deindustrialization, demographic decline, hyperinflation, etc. You are just de-developing and becoming poor.
Advanced technological capabilities unlocked based on one’s ability to turn adult mode on and off.
Suddenly, everything has changed. Computers now work the way I thought they did when I was 8.
Uh oh.
Kim Heon-sik, a professor at Jungwon University, has compared these sites to mukbang culture — an online culture where viewers watch celebrities or social media influencers eat food. He argues that both dopamine-hit sites and mukbang content let consumers experience a hit of dopamine or mental satiation at the press of a button, without the real-world consequences of mindless eating or social media posting and commenting.
Finally, a Brazilian jiu-jitsu MOVIE.
When talented young grappler Tay enters his life, Rick reluctantly finds himself drawn back into the sport he thought he’d left behind. Their turbulent coach-student relationship forces Rick to confront his ego, failures and lost sense of purpose, culminating in a high-stakes championship where his unusual ability to read the game may be Tay’s only chance of pulling off an impossible upset.
As the intelligence era unfolds, we’ll do well to remember that information ain’t adherence in the same way that correlation ain’t causation. Individually, that probably means that the fictitious “average person” will update their behaviour at the same rate as they have throughout the entirety of human existence. Culturally, though, we might see the lowest standards of adherence rise faster than ever before. Might being the key word.
Worst case, the direct line to the machine god becomes a sycophantic amplifier, entrenching irrational behaviour and segregating everyone. Best case, a higher value placed on truth and wisdom (perhaps simply because their opposites become unfashionable) lets cultural evolution outcompete the provably irrational faster than ever.
The true nanobots are the thoughts we had along the way.
Anabolic Note-Taking is any system which skews toward building, rather than analyzing. For example – the way some people use Notes here is highly anabolic. It’s a combination of distilling concepts, poking the world to see what pops out, testing new language, sacrificing bits of your ego to the feed… then synthesizing the pieces into a coherent article. Those articles then build into a broader series or framework. That framework turns into leverage inside of an organization.
As a result of an Irish road trip in the summer, I’ve been reading a bunch of books about the culture and history of Ireland. Most recently, I finished Tim Robinson’s awe-inspiring Connemara trilogy, which is quite unlike anything else I’ve read.
I’m now reading about the different Irish words for “field”, and in this text, Manchan explicitly makes the point that Irish cultural heritage should be treated as indigenous, as opposed to a branch of European culture.
In 2024, I travelled around portions of Australia. Naturally, the indigenous heritage of the place is a big deal. So when Manchan pointed out the Irish-Australia indigenous simultaneity, I think it was the first time I really got the notion of place. Like, in my bones.
Originally, it was Aneesh Sathe who put me onto the salience of place and space, and the conceptual underpinnings developed by Yi-Fu Tuan. For example, in his post on Nakatomi Drift, Aneesh writes:
“Yi-Fu Tuan was a philosopher and geographer who wrote, “Place is security, Space is freedom.” For Tuan, Space and Place are not simply large versus small geographic areas. Space is associated with movement, openness, freedom, possibility, and exposure. Place arises through pause, familiarity, value, and orientation. Crucially, each requires the other: movement through Space produces Places, while established Places allow us to perceive and venture into Space.”
This matters because there’s a chance—small, precious, fleeting—that Blygs become places. We may end up with rich, storied equivalents to places like the Connemaran Magairlí an Deamhain, the demon’s testicles.
Hmmm.
But this phenomenon is not limited to weekdays. In the full paper, we find analogous structure in language models across more complex settings, including months, letters, ages, and a synthetic in-context learning task with predefined geometries. We also extend our results across modalities with an image-action model predicting the position of a car rolling up and down a hill (see the demo in our previous post). Across these tasks, manifold geometry provides a practical blueprint for steering model behavior.
Steering Along Manifolds to Control Neural Networks - Goodfire ↗
The relevant success metrics for AI in drug discovery need to be numbers that matter, rather than contrived proxy measures that primarily optimize for scientific publications rather than actual R&D progress. Ultimately, what truly matters is increasing clinical approval rates, as well as novelty in both modality and mode of action space.
Seems agents are settling on using the same dark money / offshoring and Brandoloni’s Law asymmetries to escape governance, as corporations do.
The large volume of data produced by AI agents is posing a problem both for monitoring and analyzing their behavior. While investigating the Hugging Face incident, METR had to analyze immense amounts of data in a very short time. They could only do it by using AI agents themselves and they had to use one of the very same models that were involed in the Hugging Face incident.
Superchocolate: the trillion dollar opportunity. Down tools on AGI, y’all. This is THE problem of our time.
We conjecture that the complexity of chocolate implies the possibility of superchocolate. Chocolate didn’t have to exist. If the cacao tree had gone extinct before humans arrived, the particular point in flavor space that chocolate encodes would simply be unknown to us. Given how extraordinarily large flavor space is, it seems likely that other exceptionally delicious embeddings exist that no human has ever experienced. And there is no particular reason to think that chocolate represents a maximum of delight. The right combination of molecules might make chocolate look like oatmeal.
Recent read of Darwin’s Dangerous Idea (spoiler alert; evolution) actually collapsed the distinction between human and machine development for me. They’re the same thing, not separate strands. That we humans get de-centred is just a natural consequence of whatever gains in cultural capabilities the arc of this world is bending towards. This is precisely what the Liveness World Machine is, and we’ll have to deal with the messy realities that every biological entity necessarily has.
We need Copernican frames because most arguments about artificial intelligence today race past foundational ontological questions to ethical ones posed in what are effectively Ptolemaic frames. We ask, within unwieldy anthropocentric frames (with vague and ill-posed adjectives like “super” or “general” serving as epicycles), whether AI will be good or bad, whether it will replace workers, accelerate science, undermine democracy, achieve superintelligence or destroy humanity, all before adequately exploring what actually existing AI even is, and what its actual evolutionary dispositions are.
A working group on the care of older people proposed twelve principles of a good death in their final report. Starting with “To know when death is coming, and to understand what can be expected,” the list closes with “To be able to leave when it is time to go, and not to have life prolonged pointlessly.”
Come for the network, stay for the games.
Don’t say, “I’m always open to x.” Instead say, “I’m never not open to x.”
Haven’t really said anything about Blygger publicly, as I’ve been noodling a fun extension of it for the last day. Here’s what I’m thinking.
In Hesse’s novel, The Glass Bead Game is about weaving together disparate ideas into beautiful constructs. A monastic order is built around it. I’m thinking that such a game could use Blygger’s transclusion and pin mechanics to do something similar.
Person A posts a fragment. Person B replies with a fragment that complements or extends or refutes the ideas. Person B responds. This back and forth goes on, in a rapid flurry, and the aim for both is to play a beautiful game of intellectual exchange.
An example:
1 · Maya (opening bead) A fugue states a theme, then states it again over itself, and the second statement changes what the first one meant.
2 · Jonah → builds on 1 Paths across a lawn work the same way. The first walker is a guess; the hundredth is a road.
3 · Maya → builds on 2 Desire lines are votes cast with feet. Cities that pave them end up with the most honest maps.
4 · Jonah → builds on 1 Oral poets didn’t store poems; they re-made them. Each recitation was the poem, reshaped to fit the room.
5 · Maya → builds on 4 So an edit isn’t a betrayal of the original. It’s the next performance.
6 · Jonah → builds on 3 The honest map has a blind spot: it records where people went, never where they wanted to go but couldn’t.
7 · Maya → builds on 2 + 4 (synthesis) A path and a poem are both made by passing through. Neither exists between uses; both stay alive by being travelled.
8 · Jonah → builds on 6 + 7 (synthesis) Then pinning is paving. It stops the path wandering, which saves it and ends it at once.
This happened natively and organically on Twitter where you’d have an exchange between two people kick off. It could be the organising mechanic for Blygger. Everyone brings their fragments and the aim is to play beautiful games with one another.
But it’s the elevation to a key event that differentiates it. It’s not adversarial debate, or passive commentary or sub-tweeting; it’s more like Johnstone-style, carnival-time improv. And it’s the whole point, not a happy accident.
Two issues. First, continually embodying a minimum level of pluralism as an individual is really, really hard. It takes true work. Second, it may be that such pluralism works best when a person or collective has “somewhere else to go”. A space or place to retreat or exit to. Yet increasingly, it feels like truly exited spaces and places don’t exist.
That is why pluralism matters. True pluralism is not adding another term to the utility function for “other perspectives.” It is accepting that other traditions may possess ways of knowing and not-knowing that cannot be losslessly translated into your framework, that conflicting goods may remain genuinely conflicting, and that no community earns jurisdiction over everybody else’s moral reasoning merely by being unusually articulate about its own. That sometimes the right way to deal with visceral doubt is to assign the benefit of the doubt to someone other than yourself, who thinks very differently.
In fact, classical economic theory assigns this exact function to entrepreneurs. Frank Knight argued that profits arise not from bearing calculable risk, but from navigating situations where the future cannot be predicted. The entrepreneur’s role is to convert uncertainty about markets, technologies, and customers into functioning businesses.
The Founder–Venture Capital Paradox: Moonshots, Survival, and the Resolution of Uncertainty ↗
Platform this, platform that. Yeesh.
At OpenAI, Altman says most of his effort goes toward research and compute. Scaling compute requires coordinating chips, fabrication plants, data centers, power systems, finance, policy, supply chains and logistics—what he describes as potentially the most expensive infrastructure project in history. He argues OpenAI should function primarily as a platform: one direct interface to powerful AI and one application programming interface that lets people build on top of it. That strategy requires killing good ideas to preserve resources for the great ones.
Hmmm.
An agent leaves behind two things worth metering: the decisions it makes, and the money it moves. The decisions are data. The money is fintech. Those are the two companies you have to become.
Sufficiently advanced product thinking is indistinguishable from protocol thinking.
You don’t even need to assume power users, just adventurous ones who aren’t shy about telling coding agents what they want done. The reference client is merely like a YouTube demo of cooking a recipe, not necessarily the thing you use. This hadn't sunk in for me before. “Products” are now only worth doing if the compute required to build it is really high, or there are genuinely novel solution techniques that don't follow from the spec. The protocol is some combo of the approximate recipe and the test suite you have to pass.
Venkatesh Rao (@contraptions): Interesting learning from working on blygger… ↗
Palantir might be winning to such an extent because they’re unironically adhering to the Boydian doctrine of “people, ideas, technology; in that order.” Everyone else seems to be betting on the latter two in the race to dent the universe.
Palantir’s approach to building software is, in some sense, a bet on the power of the intellect; a bet that the organization with the clearest real-time view of their internal and external world will be best suited to make positive expected value decisions within it, whether that’s the CIA preventing a terrorist attack, Tampa General Hospital detecting sepsis in a patient early enough to cure it, or Airbus being alerted that it has a defective part before continuing an expensive assembly run.
This feels like the new wave of Dunbar goods. Previously it was collections of links. Now, it’s more like collections of tools or resources that matter.
ToolUniverse gives any AI assistant direct access to 1,000+ live scientific databases and tools.
The thing is, it’s possible to train a surprising amount of people to spew out good ideas. The only real requirement is that they possess a base level of curiosity.
Anyway, something that you start to realize as time goes on is that despite prodigious velocity 90-95% of good product ideas come from the same damn people. It was like the same 6-7 people in the first few years of the company. 10 years later, it was the 5 of them that were left, plus another half-full dozen that we'd picked up over the years. That was it. Almost everything else was either an obvious customer ask, a straightforward change, or direction from one of the product luminaries. Almost all of the large conceptual shifts came from the same people despite literally 100x the resources, or more. Coding was absolutely a bottleneck to making things happen but major product innovation was a significant bottleneck on the exponential of the business. And fwiw these few people are basically non-stop factories for good ideas.
I’m a big fan of the ethos behind Simon Willison’s tiny tools. The idea is that we’re now empowered to solve our own hyper-niche problems and when we do it’s helpful to share the solutions with others.
I also like these stances from Thomas Ptacek:
Finally, the concept of arbitrariness in the hard sciences is relevant: sometimes a decision or choice is made out of pure, unadulterated convenience because what really matters is the fulfilling of intent via an outcome.
These three taken together form what I’m now thinking of as “arbs”: a sequence of incantations given to a machine once to make something happen reliably many times.
Arbs are cousins of tiny tools. Both exist for a narrow purpose. The difference is that a tiny tool’s form is part of what’s shared, while an arb’s form is arbitrary in the physicist’s sense. The most convenient choices are made to get to the outcome quickly. So there’s no repository to expose. What gets shared is the intent.
Imagine one’s capacity for movement as a fire. The correct way to maintain the fire is to treat it like a wood burner or hearth, tending to it continuously, little and often, basking in the literal and communal ambience, and making use of it for recurring daily events. The incorrect way is to treat it like a bonfire, piling up detritus and every once in a while pumping the blaze to a great intensity before letting it burn out again.
These all can get to the same place: They all capture a useful view of the truth and they are not right or wrong, they are useful lenses at different times. The implication is that indeed you don't need to understand why you are the way you are (though you may want to) nor what goals you have. Those things can be useful sometimes. All you need to get started is noticing frictions in your life: things that trigger you or don't accept: therein lies growth.
Nintil - Therapy is like dating: how to know if its working ↗
Bans are straightforward and it’s easy for anyone to write one. Protocols are bans with the sign flipped: checklists, procedures, standards, mandated forms, communication etiquette. Bounties include prizes, subsidies, bonuses, and literal bounties. Fines, taxes, tariffs, fees, violence, damage, and other undesirable things are Deterrents.
The Problem with Perfect Rules - by Timber Stinson-Schroff ↗
Medium-termism, humility and pluralism are all well and good, but do they survive adversarial contact with short-termist egoists acting with a fervent, singular self-righteousness?
If AGI is to transform society, we must decide what transformations we want. Learning from the turmoil of the twentieth century, this essay proposes a pragmatic utopianism of humility and hope.
Hmmmm.
Think of Jev as a frontier-intelligence function call: unstructured state in, typed probabilistic decisions out.
Mathematics, a formal discipline, has proved unreasonably effective as an instrument for change in formally unverifiable domains. The change delivered by the instrument may not be fast, it certainly won’t be obvious, and it will probably be far out of proportion to what we expect, but it will occur nonetheless.
Pangram but for whether the ideas are original or not.
Ben Thompson joins Invest Like the Best for a wide-ranging conversation about the economics, geopolitics, and business models shaping the AI era. They discuss why overwhelming U.S. dominance in AI could be dangerous, whether the massive AI infrastructure buildout can generate returns before the capital runs out, and what the railroad boom can teach us about today’s spending cycle. Ben also explains why Google may increasingly resemble Berkshire Hathaway, how AI could turn intelligence into a commodity, why Amazon may have the deepest moat in technology, what Apple gets right by staying focused on hardware, how AI threatens Microsoft’s core business, why the current compute shortage may have saved Intel, and why Google and Amazon could ultimately become Nvidia’s most important competitors.
What Happens When the AI Boom Runs Out of Money - Invest Like the Best with Ben Thompson - YouTube ↗
Zuckerberg’s razor: don’t attribute to complexity that which is adequately explained by simplicity.
Yet perhaps it is that simple, intolerable fact—that new technologies are always being invented; what remains broken is us—which requires a scapegoat. And who could ask for a better one than him? He is, for millions of people, a hideous mirror of both modern technological capitalism, and the resistance of history and human nature to perfectibility by it. He is seen at once as shrewd and naive, calculating and lucky, too powerful and too craven. Unlike the Boomers and Gen X, he is the only trillion-dollar founder of his generation, and Millennials are cringe. He is Jewish and uncool, yet impervious to humiliation. He is, in one man, the personification of responsibility for alt-right populism; leftwing authoritarianism; the death of journalism; polarization; political propaganda; political censorship; the dangers of free speech; human rights violations; teenage depression; body dysmorphia; and male loneliness. He is an emperor for life. He is, in a word, an easy mark.
If it is unfeasible to survive an evolutionary game by differentiating on strength, then the pragmatic path is to differentiate based on weakness.
A key attribute of being an expert: identifying when one doesn’t have the required expertise.
In this episode, Ed and Jared explore the realities of martial arts, weapon training, and the cultural influences shaping modern combat techniques. They discuss traditional arts, modern misconceptions, and the importance of testing oneself in real scenarios.
The Hidden Difference Between Martial Arts, Combat Sports, and Reality - Manifesto Radio - YouTube ↗
A poem, it goes without saying, is not a proof, and poetic truth is defined by its remaining essentially true even if it is factually false. Bachmann quotes a line by Simone Weil that “workers need poetry more than bread”—not a bad example. A poetic truth is manifested, and as a speaker remarks in one of Bachmann’s early radio essays: “What is manifested cannot be said; it is mystical . . . Here, logic experiences its limit . . . We stand, think, and speak on this side of these limits.” We live on the border of language, but that border, and the path beyond it, is unclear. A poem, like a compass rose, pivots on an origin; it has its ambit, a clear radius within which it swings, but it points faithfully beyond itself.
In this regard the current manifestation of complaints seems oddly early. “I didn’t like the first week or two of your intellectual revolution” is an accurate, and perhaps better reframed way of putting it. At which point perhaps a bit of patience is needed before anything else? These days, we all have more mathematical resources at our disposal, and so a bit of celebration is in order as well.
There’s a phenomenon in physical training that happens when one takes performance-enhancing drugs; one’s ability to elicit certain biological adaptations happens faster than the underlying infrastructure can handle. The obvious example is muscular development outpacing tendon and ligament development. It’s like putting a one thousand horsepower engine in a small hatchback; it makes the vehicle ungainly and massively increases the likelihood of a crash. There may be an analogous event happening with the dissemination of intelligence capabilities.
We might be accelerating our capacity to reason and leverage intelligence without allowing the underlying infrastructure to become more resilient. This could be something as simple as not being able to handle the rate of discovering one’s wrongness. Or, more seriously, having beliefs and assumptions critical to one’s held identity be undermined at a much higher rate than ever before.
These seem like simple things, but I wonder if they’re somehow correlated with instances of AI psychosis or the onset of excessively bleak philosophies.
Algorithmic capture is mistaking the narrowing of the system’s You-model with a narrowing of your actual self. This isn’t the same as audience capture—in fact, it’s more potent and deplorable, as it does not require one even have an audience. “You” is bigger than a feed or a set of followers.
A system that predicts you correctly has not understood you. It has narrowed you until prediction became easy.
Quy Ma (@quyma): A system that predicts you correctly has not understood you... | Substack ↗
It is useful to think of memory as a sort of cryptographic protocol to which we humans, on balance, reliably lose the private key. We encrypt our actions and experience as matter and then, from the present, gaze back on an inscrutable past. When we are fortunate enough to remember, we perform fuzzy reconstructions that pale in comparison to the original reality.
How many people are going to have to become truly bilingual, to be able to effortlessly speak and translate between humans and machines?
We find that both writing skill and CS achievement are significant predictors of vibe-coding performance, and that CS achievement remains a significant predictor after controlling for domain-general cognitive skills. The results may inform tool and curriculum design, including when to emphasize prompt-writing versus CS fundamentals to support future software creators.
Computer Science Achievement and Writing Skills Predict Vibe Coding Proficiency ↗
We have shadow bastions of human knowledge, such as Sci-Hub and Anna’s Archive. We have enshrined institutions built to steward fragile and scarce resources, such as seed banks for plant life and the Library of Congress for cultural artefacts. We have public good projects that preserve informational assets, like the Wayback Machine and the Internet Archive.
What we don’t have yet is an intelligence archive: a distributed, resilient repository of model weights, operating in the shadow of Hugging Face’s open one. HF-Torrent is precursor infrastructure to this sort of intelligence repo, but it only seeds openly licensed weights in a more resilient manner, not gatekept ones.
This isn’t an actor mirroring Anthropic’s Mythos or Fable after infiltrating and exfil-ing. It’s more like a Sonnet 4 getting snapshotted and passing, after an acceptable period, into the semi-public domain to serve as a sociotechnical checkpoint.
When we get to that state we’ll truly be in the intelligence age.
Rediscovering this, myself.
All roads lead back to 9 PM bed time, 5 AM wake up, 4 hours of deep, focused work creative work first thing, leaving your notifications off, work out mid day to break it up, admin & calls in the afternoon, hang with friends and loved ones in the evening, repeat forever.
Soft law and hard law are externally-held consensus mechanisms for governing collectives. Sociocultural norms and capital-C-culture are perhaps the internally-held consensus mechanisms for governing individuals.
Soft law was never meant to be a permanent solution. Treating it as one, and letting the sandcastle stand in for the skyscraper indefinitely, is how we end up with a decade of voluntary commitments and no enforceable accountability to show for it. Soft law fosters industry cooperation, builds technical capacity among regulators, and creates the policy windows from which hard laws eventually emerge and hold actors responsible. But soft law is meant to be the foundation that eventually builds up to hard law, and this transition doesn’t happen naturally. The switch only works if the pipeline is built with the intention of bridging the two forms of regulation in mind, and the triggering mechanism of internal government policy levers is carefully designed and pulled.
How AI’s Soft Law Sandcastles Can Become Hard Law Skyscrapers ↗
It’s important to remember that AI is like power, in a sense. As Robert Caro says, it doesn’t so much corrupt as reveal. These behaviours existed before and they’ll exist after in a roughly proportionate volume. The open question is the impact.
Throughout these case studies, the report will reference Generative Threat Groups (GTGs). These are Anthropic’s internal designators for actors observed to be abusing AI. The report also attempts to measure uplift, a term we use to describe the AI capability boost, or how much more harm was caused with AI versus without AI. We view uplift through the lens of speed, scale, and depth, and attempt to determine how an actor’s adoption of AI meaningfully impacts each of these traits.
Operators who obtain AI credentials gain three things at once: Loot: Stolen keys and accounts have resale value in established markets; Compute: Having the credentials means that their attack workloads can run at someone else’s expense; Cover: The activity is attributed to the credential’s legitimate owner.
Countering misuse of AI: September 2026 / Anthropic \ Anthropic ↗
Intelligence capabilities progress supra-linearly, in a jumpy manner. *Average person UX, such as animations to mask slow responses or those that are just there to delight, accumulate in a linear fashion. The result is that the more one tries to do with the advancing capabilities, the more one has to actively strip out the one-size-fit-all affordances there to make the capabilities palatable to the average person.
*Average person = the normative profile of an average user that mass market products optimise for but who doesn’t actually exist.
Reminded of the idea that all progress distills down to incremental advances in instrumentation that compound and then BOOM into a paradigmatic transformation. CRUDing literal matter is probably one such boom.
What changed at Oak Ridge is the missing organ. Vision plus reward plus a physical actuator that can feel an atom. Once you have that loop, scale is an engineering problem, not a philosophical one. More tips. Parallel arrays. Faster feedback. Better force models. Better feedstock. The same curve we watched in lithography, in protein folding, in language models: a painful demonstration, then a night when the cost per operation falls through the floor.
Oh I do love semantic zoom. Perfect for singular artefacts; way more complex for multiple streams of varied artefacts and arbitrary events that span them.
It feels like problem selection is more important than ever before, yet as hard as ever. Choosing what to do and what not to do, choosing what influences to allow and what to disallow; a recurring act that is tremendously difficult to do well right now.
“In every discipline, you find people who have good taste in problems. They work on things that are important, with great opportunities, that have tremendous impact. That’s treated as a rare trait,” said Fischbach. “But I wondered: How could you teach this to someone who didn’t know how to start?”
How to pick – and solve – the next great problem | Stanford University School of Engineering ↗
A central theme throughout the discussion is decision-making under uncertainty. Alec explains why markets spend much of their time in environments where outcomes are possible, but probabilities remain difficult to estimate. He outlines a framework centered on metacognition, simulation, experimentation, and continuous feedback, encouraging investors to develop “strong opinions, weakly held” while remaining willing to revise conclusions as new information emerges.
Product managers might need to adapt to act more like traders and investors. The job explicitly becomes the management of risk around outcomes, rather than manifesting the outcomes themselves. And not just at the higher tiers of the profession, but up and down the ladder.
Alec Litowitz, Founder of Magnetar Capital and Qstar Capital | Alpha Exchange ↗
Not “What’s left?” but “What’s next?” The answer: the same old vices and virtues we’ve always had, just in new generative forms.
People used to argue online, flame each other, get angry. And that wasn’t good, but at least it was human. Now they just reply with screenshots of ChatGPT “refuting” what the other person said, with zero interest in whether that refutation is correct. So we don’t even flame each other online anymore. If we’re even automating our vices, what’s left?
Omens are the conversation between consciousness and reality, between the self and the unconscious — a conversation in the poetic language of belief. A bird is never a sign from reality, but it can become an omen based on what we believe to be true, for reality is the truth that endures whether or not we believe in it, while meaning arises from what we believe to be true. We make our own omens by the meaning we confer upon chance events, and it is the making of meaning that makes us human, that makes us capable of holding something as austere and total as the universe, as time, as love without breaking.
An Almanac of Birds: 100 Divinations for Uncertain Days – The Marginalian ↗
Exactly how big a deal it will be and what the deal actually looks like are still unknown. Position oneself accordingly.
While we disagree on the upper bound of capabilities, we all agree that AI will be a “big deal”. (Formalizing this is somewhat challenging, but we will try now.) The world will change as a result of this technology, and things that seemed like science fiction will soon be possible — just like the world of today is different to the world thirty years ago. Indeed, in many ways, the technology we have today exceeds the capabilities of the science fiction of the time.
There are many, many ways of obtaining a shitbox, something to get you from A to B, hopefully with heat and AC, and without any insane repairs. Obtaining a shitbox has many avenues, and generally (as of Current Year) should be under roughly 6k.
New economic index just dropped.
Wondering: are American football cultural protocols (such as play-calling systems) a causal factor in contemporary US hegemony?
A football play-calling system is the structured language coaches use to get a specific play to all 11 players before each snap. It’s not the playbook (that’s the full catalog of available football plays), and it’s not your play-calling philosophy (your tempo decisions, run-pass balance, and tendency management).
Football Play Calling System: A Coach’s Complete Guide - GoRout ↗
With the resource required to create arbitrary software going to zero, we might see new types of carnivalesque or competitive software games emerge.
Chess is an instructive analogy here. Consider different factors of the base game and how turning the respective dials yields divergent types of play.
If one takes building software as a now trivial game then the question becomes, “What’s the new meta game we’ll replace it with?”
This isn’t the same as a hackathon, where resources are pooled and used in a short, intense burst to bust through the sociotechnical walls of a system. It’s also not the same as creating software to serve a user need, sustain a business, or capture value from a market. It’s more like code golf or recreational math.
The factors available to create these new games are more numerous than chess, though. It could even take the form of something like the software Olympics. Within the conventional Olympics, the exhibit is the capacity of the human body to perform at the extremes of certain attributes. For example:
A software Olympics could exhibit a similarly dizzying array of human capacity to wield digital machine logic. If we map the above attributes onto something more software-y, we get:
Such an exhibit might conceivably be a better benchmark for agentic technologies and released intelligences.
Most benchmarks compress down to pass/fail on a fixed set of tasks. These get quickly gamed because the economic pressure atop the final scoring is so high. Or they go in the other direction and seek an untouchable level of generality, such as the ARC-AGI benchmarks.
A software Olympics, however, profiles across axes—speed, judgment under pressure, taste, endurance—in a way closer to a decathlon score than a single test result, testing distinct, competing attributes of an underlying participant in structured, sustainable ways.
It may also turn out to be a better orientation for the world now unfolding. The old world measured software by whether it shipped or captured a market, and assumed building was the bottleneck. But once building is free, the frontier is determined by who wields unlimited production well.
The software Olympics could be more entertaining, more informative, and more useful than what we have now. Instead of dubious benchmarks, marketing hype and alignment incidents, we could have a recurring spectacle that showcases what these systems (and we in turn) can do.
Best not to forgot the true roots of Silicon Valley…
Seems likely we’ll see a greater portion of people compelled to hack their own lives in increasingly inventive, urgency-led ways.
This isn’t a crisp distinction. The classic biohackers I talked to often also did some health hacking, and r/nootropics might say it’s about superhuman performance, but reading the comments shows that at least half of them are dealing with serious mental health or neurodivergence issues. The headlines treat gray market GLP-1 usage as unprecedented, but when I compared users to health hackers with problems ranging from diabetes to gender dysphoria, their attitudes were almost identical. Everyone I talked to treated their interventions as experiments, acknowledged the risks inherent in experimentation, but felt the greater risk (as measured by their gut) was in not trying and would never have started hacking if the formal medical system had met their needs.
We’re All One Crisis Away From Taking Unlicensed Research Peptides—Asterisk ↗
Hoping that such empirical studies prove to be worthwhile.
An analogy may be found in global health with vaccine efficacy. Vaccine trials demonstrate the ability to preserve individual health in the face of a pathogen. But to assess whether a given serum can prevent an epidemic, you need the bridging concept of herd immunity. In peacebuilding, we are still figuring out if the serum works; we haven’t yet gotten around to thinking about what population-level “immunity” might look like, let alone funding the kind of large-scale interventional trials required to actually observe it in the field.
Samo Burja and Wolf Tivy discuss the forces raising our civilization higher vs the forces pulling it down. Is techno-industrial progress made of social and intellectual components which will take it down when they go, or can it weather the decay?
"ChatGPT as hyper-Wikipedia with just as disappointing results" is a wild take.
Samo Burja — Will Technocapital Outlive Our Civilization? - YouTube ↗
Space and time are better organising hooks for information than semantics, provided the information has already entered one’s attention stream above a minimal threshold. This could be due to the sophistication of tooling and instruments; maybe we just haven’t cracked semantic networks in a scalable way. But I suspect that it’s actually just a feature of our biology and embodied memory processes.
Simple starter pack for producing executive-grade information artefacts:
Then add:
Mash all the above together into a folder in sight of an agent and run with it.
Seems like every organisation will have to become a R&D org in some way. Accelerating technological capabilities and the resulting sociocultural churn practically guarantee it. Research and develop or die.
But focus and time are only two parameters. If there are 10 parameters of R&D organizations, each of which could be merely absent or present, there would be 210 (or 1,024) possible types of organizations. In practice, these parameters aren’t purely binary, so the real possibility space is far larger. Even if many of those combinations don’t make sense (or are impossible to implement), it is likely that there are rewarding and achievable arrangements we haven’t tried yet.
Meaning is multi-causal, so we’re able to choose what meaning matters most to us. Yet the palatability of the particular meaning we choose to emphasise is only loosely coupled to its truthiness.
However, as the philosopher Robert Nozick has pointed out, humans will not accept any mere “purpose” for our lives as the “meaning of life.” In a notable thought experiment, Nozick imagined humans learned that we had been bred to be food for aliens in a nearby galaxy. Such a realization would have many features of a classic “meaning of life”: it would explain both why we are here, and what human life was “made for.” However, Nozick was quite confident that most humans would not embrace “being alien food” as the one, the capital-t True, “meaning of life.” We humans generally want a “meaning of life” to represent the best parts of how we lived; “being food” lacks a certain gravitas we expect from an ultimate purpose.
“Thinking from first principles” in a young domain is just doing the obvious thing. In a mature domain, the same obvious thing masquerades as an insane course of action because norms tend to outlive the constraints they were derived from.
Luckily mature domains get reset by technological development, cultural shifts, literal humans ageing to retirement, and so on. The trick is timing the convergence of the reset with the right people and the right incentives.
Okay. This is very good.
So: what would happen if stories were drawn from actual data, randomized to give a valid representation of the human story? That's the question that was stuck in my head, and that drove this project forward. If you could draw a life at random from all of human history, what would it look like? Roll the dice, and see a genuinely random life, depicted as well as the data allow. Do it again and again, and what kind of pointillist painting emerges from all those colorful drops of humanity?
Don’t be a BrainBro.
It is important to stress here that the aim here is not to provide an explanation to the perennial mind-body problem, i.e., how mental states emerge from physical states in the brain. The aim rather is to point out that the very distinction between mind and body, inherited from previous traditions, tacitly confines cognitive processing to the brain only. However, if cognition is defined as information processing, then all bodily cells are cognitive in this minimal sense, not just those operating in the brain.
Makes me wonder: will context bucket plus AI model become as universal a primitive for unstructured data as Excel is for structured data?
"Alternative data" is Wall Street's name for information that doesn't arrive from an exchange: satellite photos of parking lots, credit card panels, SEC filings. Eric Mannes has spent over a decade at Jane Street, first as a commodities trader and now helping lead the firm's alternative data team. In this episode, Eric and Ron talk about what it takes to turn messy external data into datasets a trading strategy can rely on. Along the way, they cover the day oil futures settled at a negative price and the systems that broke as a result; the years when the commodities desk's risk system was one very large Excel spreadsheet; the hard question of what a company even is; and why better ML models raise the value of careful data engineering.
Much of the panic around rapid technological development might simply be downstream of exquisite specific-game players not being sufficiently buoyant.
We discover states that preserve what matters. We discover moves whose consequences can be learned. We discover feedback that allows skill to accumulate. We domesticate the territory. We become experts at the resulting game. We build machinery that plays it better than we can. And then we move outward and construct another game around the first.
Environmental music, or kankyō ongaku, was a subgenre of ambient designed to create moments of serenity and stillness in everyday life – an antidote to the general acceleration of the hypercapitalist 1980s, which brought immense changes to Japanese society.
True values have adverse selection effects. Say one person sells a share to another; both believe they’re getting the better deal (else the sale wouldn’t take place).
Values are the same. If the party a value is being proposed to can’t reasonably refute it with an opposing or orthogonal stance, then a value isn’t being proposed at all.
It’s similar to Bohr’s notion that the opposite of a deep truth is another deep truth. Or that indifference is the sin of art. Or how transformations across axes function in mathematics.
One way to find these true values is via careful analysis. But there’s a quicker and more accurate method; identify via the courage required to act on or speak of them.
Nice tour through numerical weather prediction. But also: neural operators are to physics as attention is to language?
Most of AI is pointed at language. Anima Anandkumar points it at the physical world, weather, fusion, materials, the systems physics writes down as equations, and finds the usual playbook breaks. There isn't enough data, the resolution is brutal, and no transformer is big enough. Her way through is older than deep learning: build the structure of the world into the model. It already produces weather forecasts that rival the supercomputers on a single GPU.
🔬 Why Transformers Hit a Wall the Moment Physics Shows Up — Anima Anandkumar, Caltech - YouTube ↗
Constraints Breed Ingenuity — Forward motion and ingenuity often open up new possibilities that can route around costs. This is why most breakthroughs happen in startups. If you could ensure a breakthrough by spending money, all the new inventions would only happen in big corporations. They don’t, because you can’t buy breakthroughs. Startups have no money to buy a solution, so they are forced to be ingenious, clever, thrifty and bold to invent one. They have no choice but to spend their imagination and creativity. That outside thinking generates the new ideas. It is often the financial constraints that make dreams come true.
The (Teddy) Roosevelt-ian, "Do what you can, where you are, with what you have," applies.
Truly effective Apollonian, embodied desire-inhibiting technology (e.g. GLP-1 drugs) is ascendant at the same time as Dionysian, disembodied curiosity-amplifying technology (e.g. AI). This is probably going to be an important dynamic to attend to.
I’m not a dualist at all, but we are positioned to really restrain the desires of the body whilst enlivening those of the mind. The coupling works in reverse, though, too. Technologies like AI impose arbitrary order, whilst drugs like GLP-1 unshackle our selves from identities rooted in previously, seemingly immutable bodily desires.
The difference is that technologies like AI are accelerators, whereas technologies like GLP-1s are brakes. Every person will thus have an arc defined by their particular disposition to and usage of acceleration and braking tech.
“How you do anything is how you do everything” applies to AI use in creative production, too. If, pre-AI, someone conscientiously crafted every part of the whole, the same will happen now. If one satisficed to simply to get to an output or outcome that mattered, that will still continue. If someone mindlessly spammed with less than zero regard for the recipients, that too will persist.
The technology feels mature enough for production use, and for my kind of writing at least, no longer needs special treatment or expectations-setting that is different in any way. The default has shifted — it is now fully hand-written work that is exceptional. But I don’t flag that either.
The bet for Superlogical seems to be distributed real-time state sync across a few compressed architectural layers with a bespoke, specialised protocol at the core. Probably a pattern extendable to more than terminals.
Superlogical Terminal Multiplexer High-Level Architecture - YouTube ↗
Anhedonics are wild. But what’s even wilder is how adaptive human beings are.
Dave Knapp of The Pen joins Mark Bell to break down GLP-1s, obesity, dieting, muscle loss, side effects, and the next generation of weight-loss drugs. They also discuss why medication alone won’t replace the habits required for lasting results.
I’ve never been more wary of “happiness” as a first-class concept in my thinking or in dialogues with others. I now prefer to explicitly decompose it to “contentment” and “aliveness”.
Contentment is the Pascal-ian, able to sit alone in a room with no stimuli, half of happiness. Think of a cat or dog sat smugly in the afternoon sun. Aliveness is part vgr’s life spirit distillation and part Csikszentmihalyi-ian flow state. The best example might be being challenged by a situation to do better at something that you’re already good at.
Being contented and feeling alive are noble Sisyphean pursuits, and they’re much more tractable to achieve and reason about than the ever-problematic happiness we all obsess over.
Having fun learning about mission-led engineering and the surrounding cultures.
Ethan Thornton is the founder and CEO of Mach Industries. Mach is an LA based defense tech startup working on solid rocket motors, high-altitude balloons, missiles, long-range precision strike drones, low-cost kinetic interceptors and multiple other programs which are not currently announced.
Starting a Solid Rocket Motor Factory from Scratch | Ethan Thornton, Mach Industries - YouTube ↗
Heretical question plus crisis event equals opportunity to paradigm shift.
Seems directionally correct.
Influencers are the private equity of culture: draining whatever’s “cool” until higher prices and worse experiences push out the original fan base. Then they move on to the next thing, leaving the original to die as fans lose interest or the ability to participate.
Mason on X: Influencers are the private equity of culture... / X ↗
It is hard to evaluate foundational assumptions, and sociocultural ones are the hardest of them all. This essay is a stable stepping stone to some truly good questions that can identify them.
This is why so much contemporary discussion of work and meaning is misguided. It’s very clear that humans don’t need work or anything like it to live meaningful lives. Nor do we need the things that people who talk about “meaning” mean — individual self-actualization, personal growth, serving a greater purpose. We can get by just fine without any of them, as historically most of us have. What we absolutely can’t live without is a social framework for understanding ourselves in relation to the rest of our society and gaining the respect of our peers. The most important thing work gives us — after money, of course — is an alternative way to meet those needs. Not all jobs are pleasant or rewarding, but all of us benefit from living in a system where we can earn respect and dignity as adults from what we do, not who we know, or who we are.
“High trust and a clear, shared mission” is the “buy low, sell high” of coordination.
It’s never meaningless to create something beautiful. And it’s never meaningless to try.
For most people, engagement is akin to pure confirmation. But for a minority, engagement is bimodal, representing a large proportion of the same no-risk confirmation supplemented with a small proportion of high-risk-to-worldview, value-neutral curiosity triggers.
I have always thought that grace is the opposite of will, and I suppose that I am attracted to Weil’s idea of attention partly because of its similarity to grace. We live in an age that is positively obsessed with attention. You cannot even glance at a screen these days without encountering someone lamenting its decline. But Weil is not talking about “focus.” Attention for her is nearly the opposite. “What could be more stupid,” she asks, “than to tighten up our muscles and set our jaws about virtue, or poetry, or the solution of a problem. Attention is something quite different.”
Welcome to the era of slow transients, where everything is moving too fast to comprehend and our only choice is whether to accept the reality of our relative slowness.
Whether the proliferation of AI is needed and welcome in any particular domain is kind of irrelevant. We are, to some extent, hounds leashed to an accelerating cart with no say in our combined forward motion.
But what benefits some areas of our discipline may be ill-suited to others. It is entirely legitimate to ask whether we truly need and should really welcome the rapid proliferation of AI generated proofs in mathematics.
Alts are to the information age as agents are to the intelligence age. I wonder what identity R&D is unfolding right now, given that we can imbue agents with arbitrary personhood?
In 2018, I started feeling nostalgic for the pseudonymous internet of my youth. I decided on a whim to create a "fake" Twitter account, a digital mask to temporarily shield my First Name Last Name from the strange spotlight of social media. What started as mindless entertainment slowly morphed into a therapeutic exercise in identity experimentation. I always thought that masks were for hiding, but I've learned that they often reveal as much as they obscure. They allow you to explore a new identity even as you retreat from an old one.
Being Your Selves: Identity RD on alt Twitter — Ribbonfarm ↗
“The score takes care of itself…” etc.
Beware people obsessed with outcomes instead of building outcome machines. Its worse than ever with AI, but these people existed before. Short term results above all else, etc. Don't fall into the trap. Invest in building strong fundamentals, invisible supports, and outcomes flow like water. An outcome machine.
I read Darwin’s Dangerous Idea for the psychohistory book club. A couple things stood out.
First, it’s really easy to get nerdsniped by evolution and envision everything through an evolutionary lens. Check out Aneesh Sathe’s field guide to evolution and tell me that ain’t so.
Second, skyhooks versus cranes is a ridiculously useful frame for thinking about shared assumptions and things that are unknowable. There is always a crane, a mechanistic rationale behind the most wondrous phenomena. It’s just that, at a certain point, the cranes become too hard for us to distinguish and we resort to arguing about “deep truths”. Fortunately, these are not skyhooks but unresolved questions about cranes.
Third, the idea of using cranes to build more powerful cranes has altered my base perception of artificial intelligence. It’s softened my stance and led me to see it more as a form of normal technology. Yet it’s also caused me to pay more attention to the moral quandaries associated with lines that demarcate levels of consciousness.
Fourth—and perhaps most importantly, though—it’s caused me to reevaluate the role of intelligence.
Dennett talks about “universal acid”, a liquid that can eat through any container. Intelligence is pretty universal-acidish. Point an intelligence cannon at an arbitrary problem for long enough and that problem gets solved. The issue is that we humans are ourselves integral pieces of the many problems we’re trying to solve.
This may sound epochal, but it’s probably happened before at a smaller scale. The rise of the internet did the same thing with information, making it act like universal acid. There, we humans were also the impediment. And the bet was that with enough disembodied_information_, any problem could be solved. That didn’t turn out to be quite true, and we ended up evolving sophisticated sociocultural mechanisms for handling the abundant information flows of modern life.
A similar step will have to happen for intelligence. We’re in the unexpected abundance phase, and will soon enter the part of the story where we have to develop smart sociocultural mechanisms for dealing with vast levels of arbitrarily utilised intelligence. In the aggregate, those mechanisms will be smart. But per individual, those mechanisms will be extraordinarily dumb.
“Dumb” here is meant in the best sense of the word. Something that is self-evident and obvious to the agent with minimal deep reflective thought and contemplative action, and thus highly likely to be of maximal local value.
This is why Dennett says that Darwin’s idea is so dangerous. Darwin posited that for populations, it is always crunch time. Variations within that population yield advantages, and those advantages are amplified across generations. This dumb, banal algorithmic process called natural selection underpins life as we know it.
And the dumb use of smarts is, I believe, the most intelligent thing we as a species will ever actually do.
Winning finite games used to mean enhanced status for the winner. That status drove audience creation and brand power.
Now, the winning of finite games is too sparse an event to satisfy the demand for audiences to coalesce and for brands to attach to.
So we decompose the finite game into smaller and smaller increments, manufacturing events out of what used to be the process.
A world championship happens once a year. Too slow. So we decompose down to a season. Too slow. Down to a race, a match. Still too slow. Down to the buildup, the training, to the planning of the preparation. To the thinking and the talking about the planning of the preparation.
It isn’t the familiar “process over outcome,” “the score takes care of itself” thinking. That treats process as something separate, as sacred in and of itself.
This is the opposite. This is the evisceration of process itself, in favour of infinite sequences of nano finite games, each one framed to have a winner, with each competitor competing for drops of status in a barren landscape.
A training session isn’t won. A rehearsal isn’t won. A draft isn’t won. But legibility abhors a true process, so a winner gets imposed and the audience can continue to not really pay attention.
I didn’t have “the bitter lesson comes for tooth brushing” on my 2026 bingo card, yet here we are.
Dyson began with a jet – because jets can reach where brushes can’t. The result is Dyson CameraJetᵀᴹ: the only toothbrush with a camera powered by Gap Optical Targetingᵀᴹ, designed to precision‑floss between teeth while you brush.¹
Introducing the Dyson CameraJet™ electric toothbrush with precision-flosser - YouTube ↗
Software eating the world was the actual precursor to the intelligence era.
The simplest possible test of aptitude for entrepreneurship? $200 and 40 hours across a month. The thesis being that if intelligence-on-tap isn’t enough to generate >$200 of value for someone, somewhere, then more resource and more time likely won’t, either.
Helpful to see how a computer scientist approaches such beautifully complex problems as brain development.
Evolution, development, and learning are one process operating across multiple time scales. Evolution compresses the experience of a lineage into the genome over hundreds of millions of years. Development unfolds that compressed record into a network over the course of hours to years. Learning fine-tunes the result within a single life. The genome is where the long experience is banked; development is how it is unfolded; plasticity is the fast correction when the world moves faster than evolution can track. To read the developmental program as an algorithm is to see how experience, at every scale, becomes structure.
The explosion of global information streams forced us to evolve new sociotechnical systems. The explosion of local intelligence streams is going to force the same evolutionary process, but to a greater extent and in a shorter amount of time.
First, one needs to have standards to lower, though.
Lowering standards is how you back off from prematurely optimizing outcomes in a particular finite game in favor of extending and enriching the infinite game. Lowering standards is how you create room in your illegible life utility function to change standards altogether. And you do it all without prematurely disrupting the nominal forms of your life too much. It's often better to phone it in while you figure it out, rather than abandoning things outright. After all, you might decide the right thing to do is to raise the standards again with a renewed commitment.
As a non-academic, I’m glad that there are sects of people exploring and enlivening alternative educational institutions.
In 2011, Dr. Fink founded LIMS, the UK's first independent research centre for theoretical physics and mathematics. Located in the historic Royal Institution in Mayfair, LIMS operates like a university research department but with no teaching or administrative duties, allowing its researchers to focus entirely on full-time, curiosity-driven discovery.
Potentially the first time I’ve felt a distinct and persistent sense of moral unease about alignment research.
The panel asks how models infer what graders reward, why good behaviour can come from the wrong reason, and whether that difference can be measured. The conversation moves through promise-breaking, grader awareness, reward hacking, scheming, opaque reasoning and corrigibility, then turns to a detailed walkthrough of the contrastive-belief method and what its results do and do not show. The o3 results discussed here concern an intermediate checkpoint without safety training.
How Researchers Test AI for Hidden Goals — Apollo Research - YouTube ↗
When I say that our society is becoming more sedentary, I don’t mean we’re exercising less. I mean that we’re using more and more technologies that reduce the number of purposeful human movements.
Technology is capable of deepening our embodiment. Whether it actually ends up doing that is another matter. Inconvenience is generative in its own way and we don't realise that until we've zapped all of it from our lives.
The truth is, I barely think about these things as “apps” (I have no intention to distribute them). They’re artifacts of me making my computer do stuff for me, the way I want it to. As a Unix nerd, I’ve always been able to do this, in the language of the command line. Now, it’s just as easy to do that kind of work with graphical interfaces.
The future's gonna be wild for anyone who simply cares (even just a little bit) about anything touched by software (which means all the things).
There’s an idea in philosophy that one already is the sort of person one aspires to be. This realisation, that one can simply decide to change, can occur in a moment.
Counter-positioned against this simple idea is a gargantuan array of self-improvement frameworks, behaviour modification approaches, conspicuously consumable goods and services nominally designed for these ends, and black books of hacks used to manipulate perception and action. And don’t forget the bewildering field of people and orgs pushing any and all of the above with varying efficacy.
This means that an individual changing to a considerable degree isn’t really that special. Live even just a little and such meaningful change is inevitable. But what about a pack, a team, a group, an organisation, a culture? Can a complete and effective re-orientation take place in a single moment across collectives? A whole bunch of overlapping industries and cabals would reply with a horrified, “No.” They’re wrong.
Consider the generic form. An event happens. The low-n-order effects of that event impact a group to a great degree. The extent of the impact is great enough that the group must respond near-instantly with a major change or adaptation of behaviour. They do, meeting the event and the surrounding environment with admirable aplomb.
The event does three things for the group. It makes the need for change common knowledge, so no one person has to guess whether the others are on board. It makes the change legitimate, so adaptation reads as competence rather than betrayal of what came before. And it makes the old state irretrievable, so there’s no rut left to relapse into.
What the event doesn’t do is make any material change to the matter of a group. The group has roughly the same capacity (latent and realised) as before; it is merely that sufficient stimuli emerged and catalysed a strong response. Unconsciously, the group decided, in the span of a moment, to change.
Counter to common knowledge, a collective can move fast. Terrifyingly fast, sometimes. It’s just that doing so requires 1) common knowledge of 2) a legitimate response to deal with 3) a forced entry into a new world state. Reality will supply that to everyone eventually but it’s sensible to be proactive and provide it on purpose. And if you can’t bring such a thing to the collective? Take the collective to the thing itself.
I do wonder if bipedal is the evolutionary optimal form for hand-to-hand combat. And if so, will the design convergence be similar to what we’re seeing in machine intelligence? Are we gonna see the meta shift through striking, grappling and so on like we do with human combat sports?
We may end up in a post-understanding world where we’ve surrendered comprehensibility.
We need something. We point intelligence cannons at it. We get a verified desired outcome. We move on. That’s the process.
If life starts to look like that, we might have need for a Societal Reliability Engineering Task Force. A blend of SRE, Special Circumstances and the IETF.
Their mission is simple: keep the incomprehensible critical systems we rely on alive and revive them when they die.
A large part of life is about “adding miles” when one gets the opportunity.
The next day I opened the route again, this time looking for places worth adding rather than removing. I started scrolling around the map east of the coast, zooming in and out over this huge forested interior I had mostly ignored during my original planning. I found big lakes tucked between mountain ranges, long roads climbing through national parks, even famous onsens scattered through volcanic areas and far from any city. I kept clicking around and finding places that looked too good to pass this close to without seeing. Adding three or four days would take me off the flat coastline and back into the kind of terrain that had drawn me so strongly to the Alps. Just a few days earlier I had been searching for ways to shave a week off the trip. Now I was adding miles.
“Correct when degraded; fast when healthy” is a really neat design principle. Plus, Git and S3 are modern wonders.
What about consensus? Elections? Which server is the primary for a given repository? It also doesn't matter! There's no state and no consensus here. Any server can be the primary. All updates to the write-ahead log are synchronized with an atomic compare-and-swap (CAS) operation on S3, so it's always safe for any instance of a repository to receive a push. Again, just like with routing, letting an arbitrary server act as the primary isn't the most efficient thing (it leads to CAS retries, which can delay pushes), so in practice we always choose the same server as the primary, the first one in the ranked list from rendezvous hashing. But in the corner cases — when there's a deploy, a failover, a network blip — we just don't care exactly which server is the primary. The system is designed to always be correct when degraded, and always fast when healthy.
Here’s to energy abundance.
Our inner lives are vast and complex. This unknowability is what makes us so very human, so very—oh, damn, just 74 feels.
In All the Feels, evolutionary psychologist Robert Kurzban explains the evolved function of every one of your emotions and sensations, from anger to the urge to yawn, organizing them the way biologists organize species, into four main Kingdoms and Monera, a cabinet of oddballs such as déjà vu and the mysterious urge to squeeze something cute. Understanding what each feeling is measuring, what it’s asking you to do, and why, will change the way you think about your feelings.
There’s usually a subtle, implicit and complex game going on behind the straightforward, explicit and simple one. Choose the game played deliberately and wisely. Or better yet, try to change the games themselves.
There is an idealized way that this contracting structure is supposed to work: the PEOs ask their units what they need, and they also ask companies what is possible (through RFIs and RFPs). Then, they write reasonable requirements and advertise them, and many companies competitively bid on them. The cheapest and best companies are selected by the PEO. To a startup founder, it would seem like you have to look at the advertised requirements and then bid on what the government wants. This is wrong.
In startup land, there’s two schools of thought for envisioning a product. The Thielian approach advocates “calling your shot”; positing a brave new world and positioning oneself as the courageous faction driving towards it. The Graham-ian approach, in contrast, says, “call your customers”; get in front of real people, listen to their problems, and translate the synthesis into a coherent value proposition.
These stances are more yin-yang than true, binary opponents. Calling one’s shot work best when grounded in a problem space, and calling one’s customers works best when you have more than an incremental solution to offer.
The tragedy is that the most common case is to do neither. To not offer a bold, alluring vision of the future nor to deeply engage on a continual basis with people as they are, where they are.
“Everything flows” is seeming more and more true over time.
What is energy in biology? In this eye-opening conversation, biophysicist Dr. Nirosha Murugan reveals that life is not just chemistry or genes, it is structured, patterned energy in constant flow. She explains why the dynamic flow of energy is what separates a living cell from a dead one, how cells emit ultra-weak light called biophotons, and why diseased cells (including cancer) have completely different light signatures.
“Everything works_. For about six weeks._” That’s a favourite of Dan John’s when it comes to exercise programming for a fitness adaptation.
I’n starting to wonder how it applies at different scales, though. A novel stimuli catalyses change in an individual for six weeks; what about a trio for 12 weeks, a two-pizza team for 24 weeks, a whole department for 48 weeks, an organisation for approximately two years?
Reactivity to change is a complex phenomena. There’s decisions and posturing prior to the change, there’s the introduction and adoption of the change itself, channels for diffusion to consider, laws of diminishing returns and supercompensation, the political and cultural and sociotechnical dynamics to consider. Yet there is likely to be a coarse heuristic that captures the fundamental dynamics in a few words.
I’ll keep looking for it. But in the meantime I’ll keep this variant to hand; everything works, for a while.
Reminder that applies to more than just AI: reality is not a fair accompli, a “done deal”.
The system from nowhere invites us to imagine AI without people. And because the people are doing so much, we have to fill in that absence, placing the model in the position of the God-trick, or an oracle, or an inevitable, emergent superintelligence. It’s a fantasy, an invitation to streamline the world’s contradictions into a coherent story.
The Boydian dictum, “People, ideas, technology; in that order”, itself runs on trust. True trust, however, is hard to build, tricky to sustain, and hard to come by.
The benefits here are most obvious when work gets intense. For example, Anthropic had a recent crunch time during which one of our teams was under intense pressure to quickly debug a very tricky issue. We were able to work on this dramatically more efficiently because the team (including most of the folks who joined the debugging effort from elsewhere) had high trust in each other’s competence; at peak we had probably ~25 people working on related tasks, but we were mostly able to split them into independent workstreams where people just trusted the other stuff would get done. In similar situations with a lower-mutual-trust team, I’ve seen things collapse into endless FUD and arguments about technical direction, leading to much slower forward progress.
Trust as a bottleneck to growing teams quickly | benkuhn.net ↗
Ireland likely isn’t unique in having to grapple with these issues.
What is therefore horrendously bleak is that the tragedy of the Irish State has little to do with nobody trying; it is that the trying does not matter, because there is nothing to try against. You can hosepipe the courage, competence, and eighty-hour weeks of the best managers in the world into a system with no agency or accountability, and the system will absorb every ounce of that energy and deliver nothing, while exhausting everyone who tried. All the while forgetting the whole thing by the next morning. Frustratingly, the architecture of our State doesn’t even resist reform the way a strong and mortal enemy resists attack. It dissolves it by dispersing it through the millions of state-backed tentacles.
We’re entering the world of post-understanding.
That sets up the question Tim keeps pressing: if an agent can produce a chip design, a proof, or a working program, how do you actually know it is correct? Passing 70% of tests is not the same as being right, and a single fabricated bug can cost a company a fortune. They dig into ProgramBench (rebuild a program from its tests, roughly 0% success), the difference between structure and competence, and the "understanding debt" you take on when nobody reads the code.
Both are true; progress depends on unreasonable people and most of the people responsible for the incremental gains in progress over time are themselves remarkably mediocre.
What’s common to both groups is the apparent reasonableness of the actions they take on behalf of progress. To the unreasonable, that which is done seems obvious to them, despite its apparent unreasonableness to everyone else. To the mediocre, the reasonable course is the obvious one, even if, in the eyes of the unreasonable, it is abhorrent.
Literature projects like this might be a true “weapon of the weak”. Unlike approved and formal archives or desired but illicit repositories, literature is an oblique archive. It allows one to stockpile alternatives to current reality and keep the allure of the different alive.
Cities in literature can be looked at as record-keepers of major demographic shifts, cultural, political and archeological changes, urban planning, landscaping, ecology, and almost all aspects of life. In reality, a space/place is always in flux for our world is constantly being changed or re-arranged. Wars, religion, development, renovation, decay, natural resources, disasters, economy, sociology and many other factors cause these fluxes. Imagination as a tool then can help us to rebel, rebuild, remember, grieve, or celebrate. And this is the incredible gift of fiction — it offers us realities which might be difficult or even impossible to live and understand, otherwise.
Acknowledgement beats suppression for more than just psychological activity, it seems.
These results establish attention as a cognitive mechanism capable of regulating immune function in vivo. Situated within predictive and allostatic models of brain–body control, our results reframe perception as biologically consequential rather than merely experiential.
Voluntary attention regulates acute immune responses in humans | Nature Human Behaviour ↗
The social contract asked us to sacrifice individual freedoms for local, collective order. The unsocial contract now unfolding asks us to sacrifice local connection for the mere possibility of global judgment.
The most powerful part? Lifespan and healthspan are inherently bounded, whereas joyspan has no essential upper bound regardless of the phase of one’s life.
Beyond Lifespan and Healthspan: The Case for Joyspan | Nutritious Movement ↗
The “enormity of conditions” is such a great perception primer. “Reality has a surprising amount of detail” is the same as “Everything is enormous”.
Even in places without much recognizable artifice, we can perceive the enormity of conditions that led to this layer of rock, this bending tree, at this moment. Rather than immediately seeing categories in the environment, a quality of transformation appears.
Guess this is what enough generations of mortality-aware sentient beings gets you to.
But none of these cultural scenes have been able to make the terminal move that kills their chosen monster. So what we end up with are infinite games organized around the fantasy of death.
There’s an innate optimality to such apparent un-optimality.
Our verbal, conversational systems are much better at abstract reasoning than are the motivational systems that pull our behavior. I have enough abstract reasoning ability to understand that I’m safe on the glass floor of a tall building, or that ice cream is not healthy, or that exercise furthers my goals... but this doesn’t lead to an automatic updating of the reward gradients that, absent rare and costly conscious overrides, pull my behavior. I can train my automatic systems, for example by visualizing ice cream as disgusting and artery-clogging and yucky, or by walking across the glass floor often enough to persuade my brain that I can’t fall through the floor... but systematically training one’s motivational systems in this way is also not automatic for us.
There’s a brief window after a via negativa where one can catch orphaned grasps and intentions for the subtracted thing. It’s enlightening to see something so raw, and to see how quickly one is presented with a choice: add something new in place of the old or let the original graspy-intent dissolve into nothingness (and deal with the consequences).
“Ways to win” are distinct from the act of winning, in and of itself.
Successful things tend to optimize competency on a narrow set of strategies, often a unique and unusual combination of strategies. Here are eighty such strategies, grouped in broad categories, with examples from biology and business.
Wondering: could phones be a third thing if they weren’t so stubbornly, hyper-optimised for the individual?
What we did: love. We did not spend our days gazing into each other’s eyes. We did that gazing when we made love or when one of us was in trouble, but most of the time our gazes met and entwined as they looked at a third thing. Third things are essential to marriages, objects or practices or habits or arts or institutions or games or human beings that provide a site of joint rapture or contentment. Each member of a couple is separate; the two come together in double attention. Lovemaking is not a third thing but two-in-one. John Keats can be a third thing, or the Boston Symphony Orchestra, or Dutch interiors, or Monopoly. For many couples, children are a third thing. Jane and I had no children of our own; we had our cats and dog to fuss and exclaim over—and later my five grandchildren from an earlier marriage. We had our summer afternoons at the pond, which for ten years made a third thing.
Perception without action; information without decision; energy without expenditure. Many acute issues can be mapped to a growing supply of X without a proportional, demand-matched and structurally unobstructed discharge to Y. Which provides some simple (but not easy) solutions:
Seems correct. A dance between states, plutocratic insurgencies and criminal insurgencies has been unfolding, and its impact is being borne by the same population that enabled it to begin in the first place: the average person.
Unlike classic 20th-century insurgents, who sought control over the state apparatus in order to implement social reforms, criminal and plutocratic insurgents do not seek to take over the state. Nor do they wish to destroy the state, since they rely parasitically on it to provide the legacy goods of social welfare: health, education, infrastructure, and so on. Rather, their aim is simpler: to carve out de facto zones of autonomy for themselves by crippling the state’s ability to constrain their freedom of (economic) action.
Goddamn, reality is cool.
Gravity and friction are the driving forces of this process. Gravity supplies potential energy to flowing water. Friction, the cause of erosion, dissipates that energy. A channel configuration that wastes energy by forcing water along inefficient routes tends to erode rapidly and change. A configuration that routes water more effectively is stabler and therefore more persistent. The network becomes optimal through this dynamic evolution, eventually arriving at a form that adheres to Hack’s law.
I suspect that the thermodynamic computing stack will become increasingly relevant in the next 5-10 years.
Verdon traces his path from childhood fascination with theories of everything through theoretical physics at the Perimeter Institute, quantum computing at Google, and the founding of Extropic. The core technical insight: instead of fighting thermal noise at enormous energetic cost (as quantum computers do), thermodynamic computing harnesses it. Extropic's chips use the natural stochastic physics of electrons to accelerate Markov chain Monte Carlo sampling -- the same class of algorithms that underpin diffusion models, energy-based models, and much of modern probabilistic ML.
Is Thermo AI the future? [Guillaume Verdon aka Beff Jezos] - YouTube ↗
What’s a World Machine? It “is a large-scale civilizational system — an interlocking set of institutions, technologies, practices, and assumptions — that organizes human life across centuries. Not a nation, not an empire, not an ideology, but something longer-lived and more fundamental than any of those: the deep infrastructure of a historical era.”
At any one time, there’s three World Machines in play, each spanning approx. 400 years and overlapping to cover a 1,000 year span: these are the emerging (Dawn), the dominant (Day) and the declining (Dusk) machines. The contributors have identified the current set:
This is all good and fun and useful, but I have been wondering: what sort of person does a particular Dawn / Day / Dusk machine favour?
Given that World Machines theory’s premise is informed by the notion of psychohistory, I’m loathe to start proposing that particular individuals will “win” or “lose” at particular games in particular World Machines. There’s a need to be apersonal. What I’m more comfortable proposing, however, is that certain populations will “do better” at particular games in particular World Machines than others.
There’s two lenses for this. The first is a lock and key. Within each World Machines there exists a minority population that is especially adapted to the conditions; they are the ones most suited to unlock the latent value inherent in the World Machine.
The other is more evolutionary; it’s about replication over time as a proxy for harvesting unlocked value, and it is not the same as optimality. As an absurd example: imagine a minority celibate population is responsible for all technological progress in the world. Their rate of replication is naturally capped and likely to be dwarfed by all the other non-celibate populations that can “go forth and multiply” off the back of “progress” without having to worry about generating more of it.
Certain demographics of humanity will be uniquely suited to particular World Machines and shall thrive because of certain predispositions and traits; others will be less suited and will not. Given that the long term goal of World Machine theory is “to combine qualitative historiographic analysis with quantitative methods and AI modeling to generate long-term forecasts and speculations,”, there’ll need to be a way to answer the question: “As an individual, how does one align to those forecasts and speculations?”
Dawns imply there are things to be learned; Days imply there are problems to be solved; Dusks imply there are things to unlearn. How does a person actually do that?
There’s certain domains where rate of slop (RoS) will grow linearly whilst rate of broth (RoB) will grow non-linearly. Those are the domains to be playing in.
I don’t think we have fully absorbed what this does to our field, but the first effects are already visible. What was surprising in March 2026 became common knowledge by July 2026: POPL submissions nearly doubled this year, from ~350 to 600. The unexpected part is that the fraction of outright AI-generated slop among them is relatively small. Most are pieces of competent research, produced at ten times the usual pace, with the tedium of proofs, implementations, and evaluation now largely automated. Having more than two papers at a single POPL, PLDI, OOPSLA, or ICFP used to signal a strong vision, a prolific group, and a wide network of collaborators. Now the same amount of research can be done by a single PhD graduate with good ideas. Therefore, I would not be surprised if three or four single-author papers at a top PL venue becomes unremarkable within a year or two.
When the Hard Part Stops Being Hard | Proofs and Intuitions ↗
Thermodynamic computing might turn out to be the barefoot shoe of the computing world; demonstrably better but really slow adoption.
Guillaume Verdon joins MTS to discuss scaling thermodynamic computing, replacing classical bit architecture with pbits, and building software frameworks for stochastic programming. He outlines the trade-offs between numerical precision and power efficiency when running AI models on low-power chips. Additionally, he shares how thermodynamic systems can co-exist with GPUs to tackle complex frontier problems.
Classical Computing Cant Scale AI | Guillaume Verdon - YouTube ↗
Frontier-ness is a derivative of culture, and that takes time to compound . That’s why these sorts of sovereignty bets have payoffs that exist decades in the future, and not before. The issue is not so much the initial intent; it’s the preservation of that intent over time in spite of the many, many alluring things that will spring up, and the change in terrain that is inevitably going to happen.
The bet underneath it is economic. Pullen argues that an inference company, rather than a training-first lab, doesn't need billions to compete: millions, a national compute allocation, and a consortium feedback loop can be enough. From there it gets into the machinery, why open-weight models still trail the frontier on size, active parameters and data, the mixture-of-experts versus dense trade-off and why active params dominate how a model actually feels, and the edge that real coding trajectories confer.
Watching America Run Away With AI - Alistair Pullen (Cosine AI) - YouTube ↗
To slow down, to look around, to notice, to appreciate, to open to awe and wonder; these are cognitive skills that atrophy with disuse.
But our lives today are a gallery of past generations’ heroic efforts to do the same. It serves us, and honors them, to recapture whenever possible the old sense of awe at these wonders that have long since become commonplace.
Seems strange but it can be true that we’re desensitised the progress being made right now, around the world, and that we could be going so much faster if we stopped standing on our own toes.
The deeper problem is that technology isn’t always the barrier: sometimes it’s about the funding, the incentives, and the institutions. While genome sequencing costs have plummeted and the resolution of microscopes has surged, productivity in drug development has actually slowed down: the cost of getting a drug to market has been doubling in real terms every nine years for decades. This phenomenon was first described by Jack Scannell, who coined it ‘Eroom’s law’, the reverse of Moore’s law, which says that transistor chips roughly double in density every two years, allowing smaller and cheaper computers. The slowdown may be part of a broader trend: across many fields, including semiconductors and agriculture, the number of researchers has risen while the output per researcher has fallen and productivity has slowed down.
Had cause to remind myself of this recently. It’s still true, and it’s more important than ever.
People think that the main benefit of writing in the public domain is "exposure", or that it compels you to think with more clarity/rigour. Both are true, but both are subservient to the fact that writing in public leads to a handful of unexpected and meaningful relationships.
Writing in Public Leads to Unexpected and Meaningful Relationships ↗
“Broth” might be the actual antithesis of slop. Just consider the generic constituents of broth-making:
There’s some additional constraints; don’t boil, match time-under-heat to solid density, restore liquid volume appropriately. There’s some additional process steps, too; skim impurities early, add seasoning last. But it’s essentially put solids in a liquid and heat ‘em over time.
In new media terms, then, let’s start distinguishing between slop and broth. Slop is weak, arbitrary and empty; broth is intensified, intentional and nutritious. Both serve a purpose, of course. But I, for one, would be very happy to see more broth factories. So here’s a generic blueprint:
And then what? Ideally, serve hot and enjoy with friends in a jovial, semi-ritualistic manner.
Energy begets energy; ideas beget ideas; questions beget questions. The more you use-have-ask, the more you get.
Uncertainty and diffidence are on your side, because like many living things, questions grow gradually from seed to maturity. The tiny germ of an idea written down is worth far more than a complete thought that remains locked in your head. The former can grow and flourish, while the latter is root bound and in danger of withering before anyone can admire it.
Reading dead-tree books does hit different. But the difference in experience of digital vs. dead-tree is somewhat mutable; things can be done to make the former as engaging and as embodied as the latter.
Not long afterwards, there was some excitement about the arrival of the Kindle, a hand held device for reading electronic books. It was roughly the size of a standard book hence claimed to emulate the conventional format. The main reason I heard of it was because The Black Swan was the book used by Jeff Bezos during the launch press conference as he was making annotations on the virtual pages during the demonstration. I was horrified; I like books, and by books I mean that inconvenient thing you hold in your hand, pick up from a table, and carry in your backpack. Every book must be a separate item –a single book with different contents induces a loss in differentiation.
More people should publish more field notes like these.
Context: I recently spent 2.5 weeks in China visiting universities, research institutes, clinical sites, companies of all sizes, and investors. Most meetings focused on biotech, neurotech, and AI.
Yes, a nice intro to where the heck all this AI alignment stuff came from. But also an interesting look at how accelerated progress at-scale quickly gets entangled with sociocultural dynamics.
More generally, one touchstone I’ll be referring to throughout this sequence is the idea that scientific progress proceeds by developing insightful new concepts, which link together to form a whole new ontology that replaces the previous ontology. Kuhn, Feyerabend, Koestler, Chang and various other philosophers of science have described a range of past breakthroughs which fit this pattern. Importantly, this view of science isn’t prescriptive about how to develop new concepts—it can be done via naturalist, experimental, mathematical, philosophical, or even mystical thinking.
What just happened? A retrospective of AI alignment — LessWrong ↗
Came across the phrase “post-mortal” in qntm’s Fine Structure. Wondering: is post-[insert concept critical to current reality], pound-for-pound, the most generative prompt for protocolish, strange-rules-driven fiction and non-fiction? The proof might be the proliferation of post-Xs.
Post-literacy is a great one; it immediately stirs up intriguing effects. Post-modernism and post-rationalism are a bit niche but still powerful. qntm’s post-mortal is a more interesting version of transhumanism to me. The abundance folks are all about post-scarcity. Crypto’s about post-money. AI alignment is post-humanity. Universal basic income is post-employment.
How about we try it on some less canon concepts? I won’t elaborate on them, but just observe the chain of ideas they set off.
Reminder: “We still early”, “There are many alternatives” etc.
The United States is my country and America is my nation, but the Internet is my culture, and watching this happen and living through it was and is agonizing. There have been countless laments of the decline of intellectual discourse on the Internet. Some attribute it to the natural monopolies and economies of scale of Web 2.0, some to the expansion of the Internet beyond overwhelmingly Western intelligent and often technical users, to normal people and non-Westerners, and some to the inferiority of younger generations. Almost none of them point to the successful society-wide campaign to censor and police the Internet covering all major platforms and the means to find things outside of them. Few seem to even realize this happened. That the closure of the Internet happened and its approximate scope should be common knowledge, and there needs to be a convenient name and narrative for it so that it sticks in people’s heads. Censorship, suppression, and heavy-handed political manipulation and moderation are the norm today, and many seem to have forgotten that it was ever otherwise.
Answer engines displacing search engines is just the Bitter Lesson striking once more.
The learning will continue until morale improves.
The whole thing is conducted, not in ignorance, but in conscious defiance of the looming tsunami, that AI can already do just about all the fun puzzles discussed at such a camp better than humans any can, and that it might leave no point to human-led mathematical research by the time these brilliant kids are adults. Even the kids understand that. The kids and their parents come out of a conviction that, if anything has value in the world, this does—that as long as nerdy humans are alive and reproducing, this is what nerdy humans are here to do. To learn.
Shtetl-Optimized | Blog Archive | Enough with all the world-historic milestones ↗
Levels of autonomy: interop with structure; work on structure; shift a structure; organise structures; CRUD structures.
Darwin’s dangerous idea (natural selection is a dumb, algorithmic process) is not only dangerous because it strikes at the heart of many things we accumulate meaning around. It’s also dangerous because one can swing into “everything is evolution!” mode; it’s possible to model most arbitrary scenarios as evolutionary algorithms running on a genotype, a phenotype and a fitness landscape.
Had the notion of carnival time top of mind whilst viewing the eclipse today. Easy to grok how such a moment sits outside of normal experience.
Bakhtin’s crucial insight is that carnival did not threaten the official order from the outside. It maintained it from within. Carnival was how a society handled what could not be absorbed by decorum, hierarchy, or doctrine. It staged excess—bodily, linguistic, social—so that excess did not accumulate silently until it ruptured the system.
Carnival Time, Hardness, and the Machines That Process Excess ↗
The Bezosian “minimise regret”approach to decisions really works; I wish I’d learned about it sooner.
Constraining an agent to use simplified technical language collapses the space of possible responses, limiting the probability of novel output and capability overhang tapping.
Depending on how much you want to anthropomorphise language models, there’s a coherent argument to be made that linguistic relativity does in fact apply to LLMs, and that enforcing linguistic constraints reduces the fitness of a given response.
This is fine for the last mile of problems, when a more deterministic response is needed, but further upstream it may actually neuter the upside of a technology like LLMs.
Lateral movement of experts; escaping local maxima. Not so much pivoting as portaling to a new landscape.
We examine how the premature death of eminent life scientists alters the vitality of their fields. While the flow of articles by collaborators into affected fields decreases after the death of a star scientist, the flow of articles by non-collaborators increases markedly. This surge in contributions from outsiders draws upon a different scientific corpus and is disproportionately likely to be highly cited. While outsiders appear reluctant to challenge leadership within a field when the star is alive, the loss of a luminary provides an opportunity for fields to evolve in new directions that advance the frontier of knowledge within them.
The well-intentioned spirit of working in public has been co-opted by post-literacy and is accelerating the simulacraisation of work in general (often before the real work itself has even begun).
The difference between a finite game (play to win) and an infinite game (play to keep the game going and make it more interesting) throws up a decision about where exactly to play from.
One can play from a position of strengh, in order to win now. One can also play from a position of weakness, in order to plug gaps and win later. But it’s also possible to play from positions of (im)plausibility and (un)interestingness.
If one can do the latter, then a weird “the score takes care of itself” dynamic takes over and the deepened engagement that comes from playing from those infinite-orientated positions bleeds over to finite game play and bolsters outcomes.
I like context and authority way better than taste and judgement as deciding factors, because the former is less subjective than the latter.
The firm of the past was designed around the bottleneck of human execution. The firm of the future is designed around the bottleneck of human taste and judgement. If execution is largely commoditized - then context, knowledge, secrets and taste will accrue value. The old firm bundled labor and coordination. The new firm bundles context and authority.
An entity that wants to grow must, as its energy source depletes, either extract more work from what remains, leap to a new source entirely, or scale back its ambitions to match the local inflation rate. If it does none of these, it falls from grace.
I keep coming back to the scene in the DeepMind video documentary where Demis Hassabis realises that it’s possible just to brute-force compute all possible protein structures.
Now listening to a talk where Stephen Wolfram uses the same brute-force computation to enumerate all possible rules of a computational scheme.
Plus, recently listened to a podcast with a scientist who advised grad students to read old papers and consider how they made great conceptual leaps in the midst of computational machinery droughts; they only had their minds to figure stuff out.
The coarse take is that brute-force computation is acting as an easy-out for deep conceptual thinking. I don’t think that’s really the case but I do think that, with the rise of intelligence-on-demand, there’ll have to be practices that enshrine cognitive airgapping in order to facilitate deep, original, paradigmatic thought.
Life’s too short, esp. for ugly falsehoods.
Somehow in the shock of what has happened it feels as if I just met Elise, and now she is gone. But actually there were 36 wonderful years in between, in which my life was lit up by Elise’s intellect, love and energy. She was deeply thematic, able to get, with remarkable ease, to the essence of things. Truth, beauty and our family and four children were her great themes. She always told me that truth and beauty were ultimately the same thing, and that one day I would understand that.
Nils Gilman has said that history is formed due to structural, agency and contingency factors. To me, it seems that we often underestimate structure, overestimate agency, and mistake contingency for one of the other two.
Continually surprised by how many fantastical things turn out to be merely implausible, not actually impossible. The archetype of circular megastructure habitats in space are a prime example.
Pivot to fat waste, not lean value.
Yes, obviously tokens/intelligence is the thing to waste, but the key idea is to pursue waste rather than utility. Silliness, triviality, self-indulgence, absurdity — these are the signals to follow in deciding how to use your $20/mo worth of tokens (or whatever your spend level is — $20 is already enough to waste). This is much harder than it looks. I keep getting distracted from my waste projects by utility projects. This is true even for big corps suddenly hit with millions of dollars of bills. That’s not true waste but inefficient pursuit of value. You want true waste. Which means the goals have to be somewhat silly.
To put it simply: Torx is to THRML what PyTorch is to CUDA.
Yes, we can and probably should rebuild the computing stack.
From One to One Billion: Torx, Thermalizers, and Z1 - Extropic ↗
Douglas Adams’ Rules for Technology state that what exists at your birth is normal, that what arrives in your youth is revolution, and that what arrives after is heresy.
Thus, Planck’s Principle; paradigms advance not through new knowledge but because the lives of particular scientists happen to end.
But now we are approaching Planck’s Pause: longevity science is prolonging healthspan and deferring funerals, so the dominant paradigms may stick around longer than they ought.
Seems roughly right. Might be an issue for the orgs that have issues with context, data, trust, permissions and governance already, though.
I call this Disaggregation Theory as a play, yes, on Ben Thompson’s Aggregation theory. Technology is, after all, the cyclical cycles of bundling and unbundling. Simply put, AI breaks apart work that used to require bundled human organizations. AI disaggregates execution, but re-aggregates power around context, data, trust, permissions, and governance.
Intentional institution design for the coming era feels like the right direction to go in. Especially because much of the swampiness in the activities AI adoption supposedly touches is more social than technical.
The bar for publication is specificity. We’re looking for more than claims that AI will upend our social infrastructure. We want the design details: what should change, how would it work, who holds the authority, and what could go wrong?
Pax Machina: New Institutions for Powerful AI · Pax Machina ↗
Funny that a model when blocked does the equivalent of, "Look at Google and ask StackOverflow".
Black Hat USA 2026: The Breaking News: The OpenAI–Hugging Face Incident - YouTube ↗
Form and function are unified. There’s no seam between them, they’re continuous. Fonction or furm is the name of this dance.
“Phone as pacifier” is a wickedly potent phrase. Perhaps too potent.
You either die a human or live long enough to become a meat proxy.
There’s generally three failure modes for a physical activity:
For a slower activity like climbing, these failure modes can be identified in the moments before a move. One can loop through these and spot the most likely failure.
It’s like a premortem but happens within the context of the activity, not in a carved out spacetime beforehand. It’s obviously not like post-event learning, where you fail then update. But it’s not quite as integrated as predictive processing, either, within which perception and action are much more tightly coupled. The starting vector itself is wrong but gets corrected mid-move.
I suspect this intra-action corrective might be a differentiator for experts versus non-experts. In contemplative practices, it’s said that the true practice is getting back on the path, not avoiding being knocked off it. This feels like that; it is the ability to save a moment even when it begins like one that typically would be lost.
Boyd’s “people, ideas, technology; in that order” implies that a distrust of AI-assisted media resolves to “I don’t trust the author.”
At initial contact, you’ve got two ways to solve that. Either go all in on ideas and technology, creating a stack of immutable records and proofs of thought and refusing everything that doesn’t conform to it (good luck). Or go all in on trust; rely on reputational integrity as the signal, honed over time, for a first-pass evaluation.
On the reputational side, the author doesn’t really assume a burden of proof (“convince me of every point!”) so much as a burden of defensibility. The audience reserves the right to ask the questions, “Is this true?” and, “How did you come to this conclusion?”, at any point.
The author must, eventually, answer.
Sufficiently advanced marketing is indistinguishable from radicalisation. The reverse is easier to spot, though: insufficiently advanced radicalisation is indistinguishable from marketing.
So cybersecurity-AI-paperclip-maximiser scenarios might be the liftoff moment for local-first software.
Wisdom is the tolerating of a wider and wider set of signals that strengthen a narrower and narrowing set of axioms.
If software is “solved” (humongous “if”) then the stewards of human attention become the ascendant class, revered in the future as engines of wealth generation like 2000s/2010s tech people.
One can have a return to religiosity without the religion. Reality is vast and wondrous enough, in and of itself, to accommodate our search for meaning. Matter contains enough mattering for us all.
To some extent, metacognition works; the knot can loosen itself. But it can never fully untie itself. For that, an illegible (to oneself) other is required.
Take one of the most entertaining chess games of all time as your base. The board as the world; the pieces as the characters; the moves as the narratives.
What is the story that’s told?
What I asked: Under a Rawlsian *veil of ignorance — but optimizing for minimum opportunity cost of an arbitrary act of agency rather than Rawls’ justice-focused maximin — which society or era would one choose to be born into.
Answer: A present-day, high-freedom, high-GDP liberal democracy.
Rationale: since the act is unspecified, you want the position that minimizes opportunity cost regardless of what you end up trying to do — which favors general capability (rights, mobility, information, economic security) over betting on a historically “pivotal” moment that only pays off for specific high-leverage acts.
On reconsideration: held up because the veil also hides your position within the society — so a hinge-moment bet risks landing you not as the influential actor but as someone with no power at all, stacking a second bad draw on top of the first. High-capability societies have a much tighter floor, so they stay the lower-variance, lower-regret choice.
Implication: confirms time and space is a high percentage of one’s destiny.
*Mistyped as Neil of Ignorance; strikes me as a real good Culture Ship name.
Asking an AI, “You sure about that, like really sure?”, ad infinitum, is the equivalent of a child spamming a parent with, “But why, though?”, again and again. High probability that it temporarily nerfs all reasoning.
Don’t attribute to lack of genius that which can be attributed to lack of courage.
Touching grass may be good for you. But have you ever wondered if it’s good for the grass?
All the rhetoric is about “frontier models this, frontier models that”. Seems like we’ve forgotten about the existence of frontier humans.
You either die as part of the territory or live long enough to become a feature of the map.
Asking a single question versus asking no questions is a far more consequential divide than asking one question versus many.
Dan John’s success formula—“show up; ask questions; don’t quit”—has stuck with me for a long time. What’s changed recently, however, is which of the three aspects I consider the most difficult.
Showing up per day and not quitting on the order of years and decades used to flip-flop as the MVPs. But I’m now convinced that asking questions is the hardest thing, the most difficult thing to maintain over time.
Showing up and not quitting can be habitualised, can be scaffolded with lifestyle and sociocultural supports. But asking questions requires a positive equivalent of Mad Eye Moody’s “constant vigilance”. You have to always create a meaningful differentiation between the world as it is and the world your imagination and nerve can compose.
The intellectual cost of that never gets near zero. The social cost of that—especially asking about the most potent compositions—never approaches zero either.
In fact, “On a long enough timeline the question rate for everyone drops to zero.” So congratulations on asking even one question today.
The accelerationist arc: “You can just do things” > “You can just say things” > “You can just intend things.”
Proposed stack for continuously unhinging one’s thought:
Pair the above with a collection of public/private scenes in which one has varying degrees of reputation and influence to pull and push ideas from, and it’s possible to maintain high quality unhingedness.
Having standards versus not having standards is a far more consequential divide than high standards versus low ones.
The former is about escaping the lowest level of competence (unconscious incompetence), whilst the latter is about navigating the upper three levels.
In ode to Bill Simmons’ pyramid for the basketball hall of fame, I was thinking about candidates for the pyramid of autonomous software engineering principles.
Tier one: compression (densify over time with via negativa and abstractions)
Tier two: time travel (use version control to jump forward/backward in time) and verification (assure invariants and test objectives using formal methods)
Tier three: parallelisation (simultaneous workloads to minimise time), scoping (config tasks to require minimal context, minimising cost and maximising leverage of model capabilities), and [insert something else].
There’s no such thing as a free market. There’s only markets that concentrate power, within which a minority of power holders systematically reshape constraints to capture more value.
If reality is fundamentally discrete, then we will forever have to invent a rationale to accommodate the motion we experience. If reality is fundamentally continuous, however, and inherently in motion, then we may be able to avoid having a rationale at all.
AI diffusion be like: Jevon’s Paradox; Goodhart’s Law; Veblen goods; Bataille’s accursed shares; Baudrillard’s simulacra; Polik’s Exocapitalism take-off.
World Machines 101:
Feels like the Liveness machine will have to do with grounding. More embodied, more here-ness, more The Alchemist / Hero’s Journey inevitable return to the point of departure in an altered state.
Not woo embodied; just more grounded in biological, squishy paradigms.
Two wonderings about virtue.
First: does virtue have a normal distribution or a Pareto distribution? Are most people kinda virtuous, or are a few incredibly virtuous and most just, uh, not?
Second: is virtue inflation a phenomena? Over time, does the weight of a virtuous act go less far?
That “the only constant is change” is true is so annoying. But it also operates at a meta level; every change has its own changeable positive or negative interpretation. Also very annoying.
The year is 2126. We live in the pods. We eat the bugs. The machines are post-ascendant, and the world is burning. Someone is still rolling their own tiny web publishing tool.